Abstract

In the last few years, vehicle sharing has driven a gradual switch from ownership-based private mobility to service usage as a sustainable urban transport alternative. A significant number of cities have implemented mobility sharing programs. Shared transport reduces both traffic congestion, and the need for parking space, decreasing the number of vehicles on the road. The optimization of shared mobility service sites increases potential user access, reduces transportation costs, and augments demand for this transportation modality. Car sharing is a mobility concept where the usage of a vehicle fleet is shared among several people. This is a relatively new concept of transport, with short vehicle rental periods. It provides the convenience of private vehicles without additional charges. A key success factor is the location of sharing stations. The study presented here refers to a car sharing service to be operated by a carmaker in the city of São Paulo (Brazil). This article aims to identify and to select the best places to establish sharing stations within the company’s dealer and servicing network. A geographic information system (GIS) calculates spatial distribution of potential trip demand. Two models of hierarchical facility location are used to determine ideal station locations. It also suggests potential local partners to house car-sharing stations, such as hotels and private car parks. Voronoi diagrams support the location task. The recent rediscovery of Weber’s classic unique facility location problem has also been applied. The selection criterion was to maximize demand and hence operator profit, while minimizing obstacles like the distance to stations.

Highlights

  • The world’s urban population surpassed rural populations in 2007

  • The city of São Paulo accounts for 11% of the Brazilian Gross National Product (GNP) (194.9 billion dollars in 2015) and has a human development index (HDI) of 0.805 [40]

  • The points generated from the Voronoi diagram and the application of the Weiszfeld algorithm

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Summary

Introduction

The world’s urban population surpassed rural populations in 2007. The gap between urban and rural populations is increasing, as is as the total world population, intensifying problems such as traffic jams and environment deterioration. It leads to non-planned patterns of suburban development that are difficult to properly serve with public transportation. These challenges could be handled with alternative means of transportation, like shared mobility [1]. Shared mobility consists of supplying mobility as needed, eliminating vehicle ownership. This transport strategy fosters multimodality, avoiding low utilization of transport resources, reducing parking space, traffic congestions, greenhouse gas emissions, and pollution in general [1,2,3,4,5,6,7,8]

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